Strategic Tech
MARCH 16, 2021
There are a few qualities that differentiate average from high performing software engineering organisations. I believe that attitude towards the design of code and architecture is one of them. Provide Design Training & Coaching Training can accelerate the design learning process for any engineer or architect.
O'Reilly Software
JANUARY 12, 2018
2018 marks the fourth year of O’Reilly’s Software Architecture Conference , a software engineering event focused on providing hands-on training experiences for technologists at all levels of an organization—from experienced developers up through CTOs. Building evolutionary software architecture.
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O'Reilly
FEBRUARY 2, 2020
First, the behavior of an AI application depends on a model , which is built from source code and training data. You need a repository for models and for the training data. And that’s essential: if you need to understand how your model behaves, and you don’t have the training data, you’re sunk.
O'Reilly
NOVEMBER 12, 2019
More than a fifth of the respondents work in the software industry—skewing results toward the concerns of software companies, and helping explain the preponderance of those with software engineering roles. As noted earlier, the majority of survey respondents are software engineers. Concluding thoughts.
O'Reilly
OCTOBER 19, 2021
This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. Software Architecture. This approach is not novel.
The Netflix TechBlog
DECEMBER 3, 2019
mainly because of mundane reasons related to software engineering. On the other hand, very few data scientists feel strongly about the nature of the data warehouse, the compute platform that trains and scores their models, or the workflow scheduler. The steps can be arbitrary Python code.
The Netflix TechBlog
DECEMBER 3, 2019
mainly because of mundane reasons related to software engineering. On the other hand, very few data scientists feel strongly about the nature of the data warehouse, the compute platform that trains and scores their models, or the workflow scheduler. The steps can be arbitrary Python code.
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